<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="phi-etal-2024-paying">
    <titleInfo>
        <title>Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Khiem</namePart>
        <namePart type="family">Phi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Noushin</namePart>
        <namePart type="family">Salek Faramarzi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chenlu</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ritwik</namePart>
        <namePart type="family">Banerjee</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Findings of the Association for Computational Linguistics ACL 2024</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Lun-Wei</namePart>
            <namePart type="family">Ku</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Andre</namePart>
            <namePart type="family">Martins</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Vivek</namePart>
            <namePart type="family">Srikumar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Bangkok, Thailand and virtual meeting</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Whataboutism, a potent tool for disrupting narratives and sowing distrust, remains under-explored in quantitative NLP research. Moreover, past work has not distinguished its use as a strategy for misinformation and propaganda from its use as a tool for pragmatic and semantic framing. We introduce new datasets from Twitter/X and YouTube, revealing overlaps as well as distinctions between whataboutism, propaganda, and the tu quoque fallacy. Furthermore, drawing on recent work in linguistic semantics, we differentiate the ‘what about’ lexical construct from whataboutism. Our experiments bring to light unique challenges in its accurate detection, prompting the introduction of a novel method using attention weights for negative sample mining. We report significant improvements of 4% and 10% over previous state-of-the-art methods in our Twitter and YouTube collections, respectively.</abstract>
    <identifier type="citekey">phi-etal-2024-paying</identifier>
    <location>
        <url>https://aclanthology.org/2024.findings-acl.750</url>
    </location>
    <part>
        <date>2024-08</date>
        <extent unit="page">
            <start>12628</start>
            <end>12643</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse
%A Phi, Khiem
%A Salek Faramarzi, Noushin
%A Wang, Chenlu
%A Banerjee, Ritwik
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand and virtual meeting
%F phi-etal-2024-paying
%X Whataboutism, a potent tool for disrupting narratives and sowing distrust, remains under-explored in quantitative NLP research. Moreover, past work has not distinguished its use as a strategy for misinformation and propaganda from its use as a tool for pragmatic and semantic framing. We introduce new datasets from Twitter/X and YouTube, revealing overlaps as well as distinctions between whataboutism, propaganda, and the tu quoque fallacy. Furthermore, drawing on recent work in linguistic semantics, we differentiate the ‘what about’ lexical construct from whataboutism. Our experiments bring to light unique challenges in its accurate detection, prompting the introduction of a novel method using attention weights for negative sample mining. We report significant improvements of 4% and 10% over previous state-of-the-art methods in our Twitter and YouTube collections, respectively.
%U https://aclanthology.org/2024.findings-acl.750
%P 12628-12643

Markdown (Informal)

[Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse](https://aclanthology.org/2024.findings-acl.750) (Phi et al., Findings 2024)

• Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse (Phi et al., Findings 2024)

ACL

• Khiem Phi, Noushin Salek Faramarzi, Chenlu Wang, and Ritwik Banerjee. 2024. Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse. In Findings of the Association for Computational Linguistics ACL 2024, pages 12628–12643, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.